v0.53.1

See https://github.com/qualcomm/ai-hub-models/releases/v0.53.1 for changelog.

LICENSE

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+The license of the original trained model can be found at https://github.com/PRBonn/lidar-bonnetal/blob/master/LICENSE.

README.md

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+---
+library_name: pytorch
+license: other
+tags:
+- real_time
+- bu_auto
+- android
+pipeline_tag: other
+
+---
+
+![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/rangenet_plus_plus/web-assets/model_demo.png)
+
+# RangeNet-Plus-Plus: Optimized for Qualcomm Devices
+
+RangeNet-Plus-Plus (also stylized as RangeNet++) projects a LiDAR point cloud onto a 5-channel range image (depth, x, y, z, intensity) and applies a DarkNet-53 encoder with a decoder head to predict per-point semantic class labels in real time.
+
+This is based on the implementation of RangeNet-Plus-Plus found [here](https://github.com/PRBonn/lidar-bonnetal).
+This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/rangenet_plus_plus) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
+
+Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
+
+## Getting Started
+There are two ways to deploy this model on your device:
+
+### Option 1: Download Pre-Exported Models
+
+Below are pre-exported model assets ready for deployment.
+
+| Runtime | Precision | Chipset | SDK Versions | Download |
+|---|---|---|---|---|
+| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.3 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/rangenet_plus_plus/releases/v0.53.1/rangenet_plus_plus-onnx-float.zip)
+| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/rangenet_plus_plus/releases/v0.53.1/rangenet_plus_plus-tflite-float.zip)
+
+For more device-specific assets and performance metrics, visit **[RangeNet-Plus-Plus on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/rangenet_plus_plus)**.
+
+
+### Option 2: Export with Custom Configurations
+
+Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/rangenet_plus_plus) Python library to compile and export the model with your own:
+- Custom weights (e.g., fine-tuned checkpoints)
+- Custom input shapes
+- Target device and runtime configurations
+
+This option is ideal if you need to customize the model beyond the default configuration provided here.
+
+See our repository for [RangeNet-Plus-Plus on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/rangenet_plus_plus) for usage instructions.
+
+## Model Details
+
+**Model Type:** Model_use_case.driver_assistance
+
+**Model Stats:**
+- Model checkpoint: darknet53_rangenet++
+- Input resolution: 64x2048
+- Input channels: 5
+- Number of output classes: 20
+- Backbone: DarkNet-53
+
+## Performance Summary
+| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
+|---|---|---|---|---|---|---
+| RangeNet-Plus-Plus | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 41.39 ms | 3 - 335 MB | NPU
+| RangeNet-Plus-Plus | ONNX | float | Snapdragon® 8 Elite Mobile | 58.534 ms | 0 - 329 MB | NPU
+| RangeNet-Plus-Plus | ONNX | float | Snapdragon® X2 Elite | 49.501 ms | 101 - 101 MB | NPU
+| RangeNet-Plus-Plus | ONNX | float | Snapdragon® X Elite | 100.677 ms | 100 - 100 MB | NPU
+| RangeNet-Plus-Plus | ONNX | float | Snapdragon® X Elite | 100.677 ms | 100 - 100 MB | NPU
+| RangeNet-Plus-Plus | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 74.569 ms | 0 - 457 MB | NPU
+| RangeNet-Plus-Plus | ONNX | float | Qualcomm® QCS8550 (Proxy) | 102.668 ms | 3 - 5 MB | NPU
+| RangeNet-Plus-Plus | ONNX | float | Qualcomm® QCS9075 | 159.07 ms | 2 - 8 MB | NPU
+| RangeNet-Plus-Plus | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 58.534 ms | 0 - 329 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 44.421 ms | 0 - 315 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Snapdragon® 8 Elite Mobile | 60.235 ms | 0 - 296 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 78.37 ms | 0 - 511 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 595.836 ms | 0 - 308 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 97.484 ms | 0 - 96 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Qualcomm® SA8775P | 154.76 ms | 0 - 308 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Qualcomm® SA8775P | 154.76 ms | 0 - 308 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Qualcomm® SA8775P | 154.76 ms | 0 - 308 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Qualcomm® QCS9075 | 167.36 ms | 0 - 107 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 195.519 ms | 1 - 500 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Qualcomm® SA7255P | 595.836 ms | 0 - 308 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Qualcomm® SA8295P | 171.967 ms | 0 - 302 MB | NPU
+| RangeNet-Plus-Plus | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 60.235 ms | 0 - 296 MB | NPU
+
+## License
+* The license for the original implementation of RangeNet-Plus-Plus can be found
+  [here](https://github.com/PRBonn/lidar-bonnetal/blob/master/LICENSE).
+
+## References
+* [RangeNet++: Fast and Accurate LiDAR Semantic Segmentation](https://ieeexplore.ieee.org/document/8967762)
+* [Source Model Implementation](https://github.com/PRBonn/lidar-bonnetal)
+
+## Community
+* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
+* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).

release_assets.json

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+{
+    "version": "0.53.1",
+    "precisions": {
+        "float": {
+            "universal_assets": {
+                "tflite": {
+                    "tool_versions": {
+                        "qairt": "2.45.0.260326154327",
+                        "litert": "1.4.3"
+                    },
+                    "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/rangenet_plus_plus/releases/v0.53.1/rangenet_plus_plus-tflite-float.zip"
+                },
+                "onnx": {
+                    "tool_versions": {
+                        "qairt": "2.42.0.251225135753_193295",
+                        "onnx_runtime": "1.24.3"
+                    },
+                    "download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/rangenet_plus_plus/releases/v0.53.1/rangenet_plus_plus-onnx-float.zip"
+                }
+            }
+        }
+    }
+}